
Algorithms (4th Edition).rar

Robert Sedgewick, Kevin Wayne - Algorithms (4th Edition)
Published: 2011-03-19 | ISBN: 032157351X | PDF | 976 pages | 12.60 MB
Published: 2011-03-19 | ISBN: 032157351X | PDF | 976 pages | 12.60 MB
Essential Information about Algorithms and Data Structures
A Classic Reference
The latest version of Sedgewick’s best-selling series, reflecting an indispensable body of knowledge developed over the past several decades.
Broad Coverage
Full treatment of data structures and algorithms for sorting, searching, graph processing, and string processing, including fifty algorithms every programmer should know. See algs4.cs.princeton.edu/code.
Completely Revised Code
New Java implementations written in an accessible modular programming style, where all of the code is exposed to the reader and ready to use.
Engages with Applications
Algorithms are studied in the context of important scientific, engineering, and commercial applications. Clients and algorithms are expressed in real code, not the pseudo-code found in many other books.
Intellectually Stimulating
Engages reader interest with clear, concise text, detailed examples with visuals, carefully crafted code, historical and scientific context, and exercises at all levels.
A Scientific Approach
Develops precise statements about performance, supported by appropriate mathematical models and empirical studies validating those models.
Completely Revised Code
New Java implementations written in an accessible modular programming style, where all of the code is exposed to the reader and ready to use.
Engages with Applications
Algorithms are studied in the context of important scientific, engineering, and commercial applications. Clients and algorithms are expressed in real code, not the pseudo-code found in many other books.
Intellectually Stimulating
Engages reader interest with clear, concise text, detailed examples with visuals, carefully crafted code, historical and scientific context, and exercises at all levels.
A Scientific Approach
Develops precise statements about performance, supported by appropriate mathematical models and empirical studies validating those models.
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